Data storage devices such as disk drives comprise a disk and a head connected to a distal end of an actuator arm which is rotated about a pivot by a voice coil motor (VCM) to position the head radially over the disk. The disk comprises a plurality of radially spaced, concentric tracks for recording user data sectors and servo sectors. The servo sectors comprise head positioning information (e.g., a track address) which is read by the head and processed by a servo control system to control the actuator arm as it seeks from track to track.
FIG. 1 shows a prior art disk format 2 as comprising a number of servo tracks 4 defined by servo sectors 60-6N, wherein data tracks are defined relative to the servo tracks 4. Each servo sector 6i comprises a preamble 8 for storing a periodic pattern, which allows proper gain adjustment and timing synchronization of the read signal, and a sync mark 10 for storing a special pattern used to symbol synchronize to a servo data field 12. The servo data field 12 stores coarse head positioning information, such as a servo track address, used to position the head over a target data track during a seek operation. Each servo sector 6i further comprises groups of servo bursts 14 (e.g., A, B, C and D bursts), which comprise a number of consecutive transitions recorded at precise intervals and offsets with respect to a servo track centerline. The groups of servo bursts 14 provide fine head position information used for centerline tracking while accessing a data track during write/read operations.
Data is typically written to data sectors within a data track by modulating the write current of a write element, for example, using a non-return to zero (NRZ) encoding where a binary “1” is written using positive write current (+1) and a binary “0” is written using a negative write current (−1), thereby writing magnetic transitions onto the disk surface. A read element (e.g., a magnetoresistive (MR) element) is then used to transduce the magnetic transitions into a read signal that is demodulated by a read channel. The recording and reproduction process may be considered a communication channel, wherein communication demodulation techniques may be employed to demodulate the read signal.
A common demodulation technique employed in disk drives is known as partial response maximum likelihood (PRML), wherein the recording channel is equalized into a desired partial response (e.g., PR4, EPR4, etc.), the resulting read signal sampled, and the signal samples demodulated using a ML data detector. The ML data detector is commonly implemented using the well known Viterbi data detector which attempts to find the minimum distance sequence (in Euclidean space) through a trellis. The accuracy of a Viterbi data detector matches a true ML data detector only if the signal noise is time invariant (data independent) and white (statistically independent) with a Gaussian probability distribution.
In the magnetic recording channel of a disk drive, the signal noise is neither data independent nor white, and therefore signal processing techniques have been employed to improve the accuracy of the ML data detector by compensating for the data dependent, non-white noise in the read signal. For example, the prior art has employed a bank of data dependent noise whitening filters in front of the ML detector that each attempt to whiten the signal noise based on an optimal noise-whitening function for each possible recorded data sequence. The output of each data dependent noise whitening filter is then used to compute the corresponding branch metrics in the ML detector (e.g., for each branch corresponding to the data sequence assigned to each data dependent noise whitening filter). Since the noise correlating effect of the recording channel (including the equalizer filter) is essentially infinite, the performance of each data dependent noise whitening filter increases as the length of the corresponding data sequence increases. However, the number of data dependent noise whitening filters also doubles with each additional bit in the data sequence (e.g., there are 2N data dependent noise whitening filters where N is the length of the data sequence).